DBMS > KairosDB vs. Machbase Neo vs. RRDtool vs. Yaacomo

System Properties Comparison KairosDB vs. Machbase Neo vs. RRDtool vs. Yaacomo

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Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

Distributed Time Series DBMS based on Cassandra or H2

TimeSeries DBMS for AIoT and BigData

Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database.

The data is stored in a circular buffer, thus the system storage footprint remains constant over time.

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Time Series DBMS

Relational DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.62
Rank	#239	Overall
	#20	Time Series DBMS

Score	0.12
Rank	#339	Overall
	#30	Time Series DBMS

Score	1.87
Rank	#136	Overall
	#11	Time Series DBMS

Website

github.com/kairosdb/kairosdb

machbase.com

oss.oetiker.ch/rrdtool

yaacomo.com

Technical documentation

kairosdb.github.io

machbase.com/dbms

oss.oetiker.ch/rrdtool/doc

Developer

Machbase

Tobias Oetiker

Q2WEB GmbH

Initial release

2013

1999

2009

Current release

1.2.2, November 2018

V8.0, August 2023

1.8.0, 2022

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

free test version available

Open Source

GPL V2 and FLOSS

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Implementations in Java (e.g. RRD4J) and C# available

Server operating systems

Linux
OS X
Windows

Linux
macOS
Windows

HP-UX
Linux

Android
Linux
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data only

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Exporting into and restoring from XML files possible

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

Graphite protocol
HTTP REST
Telnet API

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

in-process shared library
Pipes

JDBC
ODBC

Supported programming languages

Java
JavaScript

Node.js
PHP
Python

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

with librrd library
C#

with a different implementation of RRDTool
Java

with a different implementation of RRDTool
JavaScript (Node.js)

with a different implementation of RRDTool
Lua
Perl
PHP

with a wrapper library
Python
Ruby

Server-side scripts

Stored procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

selectable replication factor

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Concurrency

Support for concurrent manipulation of data

yes

by using the rrdcached daemon

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

volatile and lookup table

yes

User concepts

Access control

simple password-based access control

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

Time Series DBMS as a new trend?
1 June 2015, Paul Andlinger

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